ALBERT

Description: The integration of the Global Positioning System (GPS) and the Inertial Navigation System (INS) based on Real-time Kinematic (RTK) and Single Point Positioning (SPP) technology have been applied as a powerful approach in kinematic positioning and attitude determination. However, the accuracy of RTK and SPP based GPS/INS integration mode will degrade visibly along with the increasing user-base distance and the quality of pseudo-range. In order to overcome such weaknesses, the tightly coupled integration between GPS Precise Point Positioning (PPP) and INS was proposed recently. Because of the rapid development of the multi-constellation Global Navigation Satellite System (multi-GNSS), we introduce the multi-GNSS into the tightly coupled integration of PPP and INS in this paper. Meanwhile, in order to weaken the impacts of the GNSS observations with low quality and the inaccurate state model on the performance of the multi-GNSS PPP/INS tightly coupled integration, the Helmert variance component estimation based adaptive Kalman filter is employed in the algorithm implementation. Finally, a set of vehicle-borne GPS + BeiDou + GLONASS and Micro-Electro-Mechanical-Systems (MEMS) INS data is analyzed to evaluate the performance of such algorithm. The statistics indicate that the performance of the multi-GNSS PPP/INS tightly coupled integration can be enhanced significantly in terms of both position accuracy and convergence time.

Description: The GNSS derived Zenith Tropospheric Delay (ZTD) plays today a very critical role in meteorological study and weather forecasts, as ZTDs of thousands of GNSS stations are operationally assimilated into numerical weather prediction models. Recently, the Chinese BeiDou Navigation Satellite System (BDS) was officially announced to provide operational services around China and its neighborhood and it was demonstrated to be very promising for precise navigation and positioning. In this contribution, we concentrate on estimating ZTD using BDS observations to assess its capacity for troposphere remote sensing. A local network which is about 250 km from Beijing and comprised of six stations equipped with GPS- and BDS-capable receivers is utilized. Data from 5 to 8 November 2012 collected on the network is processed in network mode using precise orbits and in Precise Point Positioning mode using precise orbits and clocks. The precise orbits and clocks are generated from a tracking network with most of the stations in China and several stations around the world. The derived ZTDs are compared with that estimated from GPS data using the final products of the International GNSS Service (IGS). The comparison shows that the bias and the standard deviation of the ZTD differences are about 2 mm and 5 mm, respectively, which are very close to the differences of GPS ZTD estimated using different software packages.

Description: In recent times increasing numbers of high-rate GPS stations have been installed around the world and set-up to provide data in real-time. These networks provide a great opportunity to quickly capture surface displacements, which makes them important as potential constituents of earthquake/tsunami monitoring and warning systems. The appropriate GPS real-time data analysis with sufficient accuracy for this purpose is a main focus of the current GPS research. In this paper we propose an augmented point positioning method for GPS based hazard monitoring, which can achieve fast or even instantaneous precise positioning without relying on data of a specific reference station. The proposed method overcomes the limitations of the currently mostly used GPS processing approaches of relative positioning and global precise point positioning. The advantages of the proposed approach are demonstrated by using GPS data, which was recorded during the 2011 Tohoku-Oki earthquake in Japan. Scientific Reports 3 doi: 10.1038/srep02682

Description: The developing multi-GNSS constellations have the potential to provide accurate high-resolution tropospheric gradients. Such data, closely linked to strong humidity gradients accompanying severe weather phenomena, are considered a new important data source for meteorological studies, e.g. nowcasting of severe rainfall events. Here, we describe the development of a multi-GNSS processing system for the precise retrieval of high-resolution tropospheric gradients. The retrieved products were validated by using independent water vapor radiometer (WVR) observations and numerical weather model (NWM) data. The multi-GNSS high-resolution gradients agree well with those, derived from NWM and WVR, especially for the fast-changing peaks which were mostly associated with synoptic fronts. Compared to GPS-only gradients, the correlations with the validation data are significantly improved up to 20~35%. The new data product has significant potential to improve numerical weather prediction and to advance meteorological studies.

Description: The tropospheric horizontal gradients with high spatiotemporal resolutions provide important information to describe the azimuthally asymmetric delays, and significantly increase the ability of ground-based GNSS (Global Navigation Satellite Systems) within the field of meteorological studies, like the nowcasting of severe rainfall events. The recent rapid development of multi-GNSS constellations has potential to provide such high-resolution gradients with a significant degree of accuracy. In this study, we develop a multi-GNSS process for the precise retrieval of high-resolution tropospheric gradients. The tropospheric gradients with different temporal resolutions, retrieved from both single-system and multi-GNSS solutions, are validated using independent numerical weather models (NWM) data and water vapor radiometer (WVR) observations. The benefits of multi-GNSS processing for the retrieval of tropospheric gradients, as well as for the improvement of precise positioning, are demonstrated. The multi-GNSS high-resolution gradients agree well with those derived from the NWM and WVR, especially for the fast-changing peaks which are mostly associated with synoptic fronts. The multi-GNSS gradients behave in a much more stable manner than the single-system estimates, especially in cases of high temporal resolution, benefiting from the increased number of observed satellites and improved observation geometry. The high-resolution multi-GNSS gradients show higher correlation with the NWM and WVR gradients than the low-resolution gradients. Furthermore, the precision of station positions can also be noticeably improved by multi-GNSS fusion, and enhanced results can be achieved if the high-resolution gradient estimation is performed, instead of the commonly used daily gradient estimation in the multi-GNSS data processing.

Description: This is a great era of significant changes and innovations in the field of geodesy and navigation with the emerging multi-constellation Global Navigation Satellite Systems (GNSS) [...]

Description: Real-time multi-GNSS precise point positioning (PPP) requires the support of high-rate satellite clock corrections. Due to the large number of ambiguity parameters, it is difficult to update clocks at high frequency in real-time for a large reference network. With the increasing number of satellites of multi-GNSS constellations and the number of stations, real-time high-rate clock estimation becomes a big challenge. In this contribution, we propose a decentralized clock estimation (DECE) strategy, in which both undifferenced (UD) and epoch-differenced (ED) mode are implemented but run separately in different computers, and their output clocks are combined in another process to generate a unique product. While redundant UD and/or ED processing lines can be run in offsite computers to improve the robustness, processing lines for different networks can also be included to improve the clock quality. The new strategy is realized based on the Position and Navigation Data Analyst (PANDA) software package and is experimentally validated with about 110 real-time stations for clock estimation by comparison of the estimated clocks and the PPP performance applying estimated clocks. The results of the real-time PPP experiment using 12 global stations show that with the greatly improved computational efficiency, 3.14 cm in horizontal and 5.51 cm in vertical can be achieved using the estimated DECE clock.

Description: The multi-constellation GNSS (e.g., GPS, GLONASS, Galileo, and BeiDou) offers great opportunities for real-time retrieval of atmospheric parameters for supporting numerical weather prediction (NWP) nowcasting or severe weather event monitoring. In this study, the observations from different GNSS are combined to retrieve atmospheric parameters based on the real-time precise point positioning technique. The atmospheric parameters, retrieved from multi-GNSS observations of a 180 days period from about 100 globally distributed stations, including zenith total delay (ZTD), integrated water vapor (IWV), horizontal gradient and slant total delay (STD), are analyzed and evaluated. The water vapor radiometer data and a numerical weather model, the operational analysis of the European Center for Medium-Range Weather Forecasts (ECMWF), are used to independently validate the performance of individual GNSS and also demonstrate the benefits of multi-constellation GNSS for real-time atmospheric monitoring. Our results show that the GLONASS and BeiDou have the potential capability for real-time atmospheric parameters retrieval for time-critical meteorological applications as GPS does, and the combination of multi-GNSS observations can improve the performance of a single-system solution in meteorological applications with higher accuracy and robustness. The multi-GNSS processing greatly increase the number of STDs. The mean and standard deviation of STDs between each GNSS and ECMWF exhibit a good stability as function of the elevation angle, the azimuth angle, and time in general. An obvious latitude dependence is confirmed by a map of station specific mean and standard deviations. Such real-time atmospheric products, provided by multi-GNSS processing with higher accuracy, stronger reliability and better distribution, might be highly valuable for atmospheric sounding systems, especially for nowcasting of extreme weather.

Description: Global Positioning System (GPS) has been proved to be a powerful tool for measuring co-seismic ground displacements with an application to seismic source inversion. Whereas most of the tsunamis are triggered by large earthquakes, GPS can contribute to the tsunami early warning system (TEWS) by helping to obtain tsunami source parameters in near real-time. Toward the end of 2012, the second phase of the BeiDou Navigation Satellite System (BDS) constellation was accomplished, and BDS has been providing regional positioning service since then. Numerical results indicate that precision of BDS nowadays is equivalent to that of the GPS. Compared with a single Global Satellite Navigation System (GNSS), combined BDS/GPS real-time processing can improve accuracy and especially reliability of retrieved co-seismic displacements. In the present study, we investigate the potential of BDS to serve for the early warning system of tsunamis in the South China Sea region. To facilitate early warnings of tsunamis and forecasting capabilities in this region, we propose to distribute an array of BDS-stations along the Luzon Island (Philippines). By simulating an earthquake with Mw = 8 at the Manila trench as an example, we demonstrate that such an array will be able to detect earthquake parameters in real time with a high degree of accuracy and, hence, contribute to the fast and reliable tsunami early warning system in this region.

Description: In order to improve the precision of GLONASS orbits, this paper presents a method to connect the data segments of a single station-satellite pair to increase the observation continuity and, consequently, the strength of the precise orbit determination (POD) solution. In this method, for each GLONASS station-satellite pair, the wide-lane ambiguities derived from the Melbourne–Wübbena combination are statistically tested and corrected for phase integer offsets and then the same is carried out for the narrow-lane ambiguities calculated from the POD solution. An experimental validation was carried out using one-month GNSS data of a global network with 175 IGS stations. The result shows that, on average, 27.1% of the GLONASS station-satellite pairs with multiple data segments could be connected to a single long observation arc and, thus, only one ambiguity parameter was estimated. Using the connected data, the GLONASS orbit overlapping RMS at the day boundaries could be reduced by 19.2% in ideal cases with an averaged reduction of about 6.3%.